Many automation applications employ motion control systems to control machine position and speed. Such motion control systems typically include one or more motors or similar actuating devices operating under the guidance of a controller, which sends position and speed control instructions to the motor in accordance with a user-defined control algorithm. Some motion control systems operate in a closed-loop configuration, whereby the controller instructs the motor to move to a target position or to transition to a target velocity (a desired state) and receives feedback information indicating an actual state of the motor. The controller monitors the feedback information to determine whether the motor has reached the target position or velocity, and adjusts the control signal to correct errors between the actual state and the desired state.
Designers of motion control systems seek to achieve an optimal trade-off between various performance aspects. For example, an aggressively tuned controller may result in a system that tracks a reference position signal with high accuracy and fast response time, but experiences instabilities in the presence of system noise and or other disturbances. Alternatively, tuning the controller more conservatively will improve system stability, but at the expense of response time. The process of selecting suitable gain coefficients for the controller is known as tuning.
Turning the gain coefficients for a given controller determines the controller's bandwidth, which is a measure of responsiveness of the controlled mechanical system to changes in the control signal. The response of the controlled system to a signal from a controller is partially a function of the controller's bandwidth and the physical characteristics of the mechanical system or plant (e.g., inertia, damping, friction, coupling stiffness, resonance, etc.).
In many motion control applications, system designers attempt to tune the motion controller to optimize, to the degree possible, one or more selected performance variables or specifications that are considered particularly important, depending on the type of application being performed by the motion system. For example, in some motion control applications, maintaining a low maximum deviation may be a higher priority than maintaining a low torque noise level. In such applications, the system designer may attempt to tune the controller to minimize the maximum deviation of the system, while accepting that there may be a commensurate increase in the torque noise level (which typically increases as the maximum deviation is decreased).
The process of tuning a controller to satisfy the specifications of a particular motion control application is a challenging task. Although the dynamics of system and controller tuning are well studied, the act of tuning a control system in order to meet application specifications, taking the limits of the motion system into consideration, is still not an automated process in practice.
The above-described is merely intended to provide an overview of some of the challenges facing conventional motion control systems. Other challenges with conventional systems and contrasting benefits of the various non-limiting embodiments described herein may become further apparent upon review of the following description.